Genome-wide association study of susceptibility to<i>Pseudomonas aeruginosa</i>infection in cystic fibrosis
Bibliographic record
Abstract
Background Pseudomonas aeruginosais a common pathogen that contributes to progressive lung disease in cystic fibrosis (CF). Genetic factors other than CF-causingCFTR(CF transmembrane conductance regulator) variations contribute ∼85% of the variation in chronicP. aeruginosainfection age in CF according to twin studies, but the susceptibility loci remain unknown. Our objective is to advance understanding of the genetic basis of host susceptibility toP. aeruginosainfection. Materials and methods We conducted a genome-wide association study of chronicP. aeruginosainfection age in 1037 Canadians with CF. We subsequently assessed the genetic correlation between chronicP. aeruginosainfection age and lung function through polygenic risk score (PRS) analysis and inferred their causal relationship through bidirectional Mendelian randomisation analysis. Results Two novel genome-wide significant loci with lead single nucleotide polymorphisms (SNPs) rs62369766 (chr5p12; p=1.98×10−8) and rs927553 (chr13q12.12; p=1.91×10−8) were associated with chronicP. aeruginosainfection age. The rs62369766 locus was validated using an independent French cohort (n=501). Furthermore, the PRS constructed from CF lung function-associated SNPs was significantly associated with chronicP. aeruginosainfection age (p=0.002). Finally, our analysis presented evidence for a causal effect of lung function on chronicP. aeruginosainfection age (β=0.782 years, p=4.24×10−4). In the reverse direction, we observed a moderate effect (β=0.002, p=0.012). Conclusions We identified two novel loci that are associated with chronicP. aeruginosainfection age in individuals with CF. Additionally, we provided evidence of common genetic contributors and a potential causal relationship betweenP. aeruginosainfection susceptibility and lung function in CF. Therapeutics targeting these genetic factors may delay the onset of chronic infections, which account for significant remaining morbidity in CF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".